code: def _get_config(self, skip_param_schedulers=False):
      return {
          "loss": {"name": "CrossEntropyLoss"},
          "dataset": {
              "train": {
                  "name": "synthetic_image",
                  "split": "train",
                  "num_classes": 2,
                  "crop_size": 20,
                  "class_ratio": 0.5,
                  "num_samples": 10,
                  "seed": 0,
                  "batchsize_per_replica": 5,
                  "use_shuffle": True,
                  "transforms": [
                      {
                          "name": "apply_transform_to_key",
                          "transforms": [
                              {"name": "ToTensor"},
                              {
                                  "name": "Normalize",
                                  "mean": [0.485, 0.456, 0.406],
                                  "std": [0.229, 0.224, 0.225],
                              },
                          ],
                          "key": "input",
                      }
                  ],
              },
              "test": {
                  "name": "synthetic_image",
                  "split": "test",
                  "num_classes": 2,
                  "crop_size": 20,
                  "class_ratio": 0.5,
                  "num_samples": 10,
                  "seed": 0,
                  "batchsize_per_replica": 5,
                  "use_shuffle": False,
                  "transforms": [
                      {
                          "name": "apply_transform_to_key",
                          "transforms": [
                              {"name": "ToTensor"},
                              {
                                  "name": "Normalize",
                                  "mean": [0.485, 0.456, 0.406],
                                  "std": [0.229, 0.224, 0.225],
                              },
                          ],
                          "key": "input",
                      }
                  ],
              },
          },
          "model": {
              "name": "mlp",
              # 3x20x20 = 1200
              "input_dim": 1200,
              "output_dim": 1000,
              "hidden_dims": [10],
          },
          "meters": {"accuracy": {"topk": [1]}},
          "optimizer": self._get_optimizer_config(
              skip_param_schedulers
          ),
      }
  
imports: import unittest
  from unittest.mock import Mock
  from classy_vision.dataset import build_dataset
  from classy_vision.hooks import ClassyHook
  from classy_vision.losses import build_loss
  from classy_vision.models import build_model
  from classy_vision.optim import build_optimizer, build_optimizer_schedulers
  from classy_vision.optim.param_scheduler import ClassyParamScheduler, register_param_scheduler, UpdateInterval
  from classy_vision.tasks import ClassificationTask, ClassyTask
  from classy_vision.trainer import LocalTrainer
label_desc: Use image node_id 2 for calling the TestParamSchedulerIntegration obj's underlying member method code with example usage: obj._get_config(skip_param_schedulers) and returns: dict